In recent years many online search features have begun to pivot around entities. Entities are instances of abstract concepts and objects, including people, events, locations, businesses, movies, and the like. Entities generally include one or more attributes, each attribute having at least one associated attribute value. Some search engines, for instance, the BING search engine available from Microsoft Corporation of Redmond, Wash., are capable of powering scenarios to explicitly search for a specific entity instead of just a text description of the entity. For example, such a search engine may be capable of recognizing “John Doe” as an entity and thus of providing a richer search result experience for specifically this entity over the search experience it could provide for a textual query such as “john doe.”
One key challenge for performing Web ranking for specific known entities is to maintain a database of known attribute values associated with such entities (such as the employer associated with a person entity, the location associated with a restaurant entity, and the like). Some solutions have focused on mining crawled Web content, via the use of templates for example, for creating such databases. Often, however, these databases suffer from missing or ambiguous attribute values that are either not present on the Web or could not be successfully extracted and/or associated with the relevant entity.